Terrorist Group Adaptation & Lessons for Counterterrorism (TERGAP)
Terrorist groups find ways to adapt to changes in their environment to stay relevant and powerful. This project, Terrorist Group Adaptation & Lessons for Counterterrorism (TERGAP) offers new insights into this phenomenon by developing a theory of terrorist group strategic target selection and applying big data analytics and machine learning common in brain sciences, natural sciences, and bioinformatics to test the hypotheses. First, to understand why terrorism is a persistent problem, we first need to understand how terrorist groups are making strategic decisions and using violence to accomplish recruitment and support building goals. This is crucial because without new recruits and supporters, terrorist groups die. Second, because terrorist groups can also adapt to changes in counterterrorism, this project proposes to build two cross-national data collection efforts that enable big data analytics to identify adaptation patterns. The first focuses on counterterrorism policies and the second, using natural language processing, focuses on counter-terrorist events.
Project: Terrorist Group Adaptation & Lessons for Counterterrorism (TERGAP)
Funder: European Research Council (Starting Grant)
Duration: January 1, 2024 – December 31, 2028
Terrorist groups find ways to adapt to changes in their environment to stay relevant and powerful. This project, Terrorist Group Adaptation & Lessons for Counterterrorism (TERGAP) offers new insights into this phenomenon by developing a theory of terrorist group strategic target selection and applying big data analytics and machine learning common in brain sciences, natural sciences, and bioinformatics to test the hypotheses. First, to understand why terrorism is a persistent problem, we first need to understand how terrorist groups are making strategic decisions and using violence to accomplish recruitment and support building goals. This is crucial because without new recruits and supporters, terrorist groups die. Second, because terrorist groups can also adapt to changes in counterterrorism, this project proposes to build two cross-national data collection efforts that enable big data analytics to identify adaptation patterns. The first focuses on counterterrorism policies and the second, using natural language processing, focuses on counter-terrorist events.
Project: Terrorist Group Adaptation & Lessons for Counterterrorism (TERGAP)
Funder: European Research Council (Starting Grant)
Duration: January 1, 2024 – December 31, 2028
